A rapid prediction algorithm suitable to portable device for animal body-temperature measurement - Zhu, Qi-Wen; Gu, Bin; Ji, Liang; Sun, Dong; Liu, Yu-Dong; Yu, Bao-Ming (Journal of computational methods in sciences and engineering, 2022)
The body-temperature is the most significant vital signs of human and animals. It is easily imaginable that measurement of body-temperature of animals will be much more difficult than that of human being due to lack of endurance or fear of measuring instrument. Infrared temperature measurement device may be a solution, however coverage of hair and fur may incur a large error. To address this issue, a rapidly executed algorithm is developed for prediction of steady state body temperature, which needs only a few one-tenth of measurement duration that the currently popular machine learning-based approach usually requires. Let a cubic function c ⁢ ( t ) fit the sampled temperature data which are generated by the measurement within a significantly short duration from t n - k to t n , k > 0 . Then let a quadratic function f ⁢ ( t ) = a 2 ⁢ t 2 + a 2 ⁢ t + a as a prediction function go through the point ( t n , c ⁢ ( t n ) ) and share the same slope of s n thereat. Finally try to find a next point ( t n + m , f ⁢ ( t n + m ) ), m > 0 , where the slope satisfies s n + m = s n / 2 and m depends strongly on s n through an empirical formula. Accordingly, f ⁢ ( t ) can be determined by ( t n , c ⁢ ( t n ) ), s n and s n + m . Experiments indicate that the maximum of f ⁢ ( t ) approaches well the steady state temperature of the measured subject with a quite small error.